Dec 122013
 

TightClust 1.0

:: DESCRIPTION

TightClust applies K-means clustering as an intermediate clustering engine. Early truncation of a hierarchical clustering tree is used to overcome the local minimum problem in K-means clustering. The tightest and most stable clusters are identified in a sequential manner through an analysis of the tendency of genes to be grouped together under repeated resampling.

::DEVELOPER

George C. Tseng 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 TightClust

:: MORE INFORMATION

Citation

George C. Tseng and Wing H. Wong. (2005)
Tight Clustering: A Resampling-based Approach for Identifying Stable and Tight Patterns in Data.
Biometrics.61:10-16.

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